InTune: Reinforcement Learning-based Data Pipeline Optimization for Deep Recommendation Models
Kabir Nagrecha, Lingyi Liu, Pablo Delgado, Prasanna Padmanabhan · 2023
Deep learning-based recommender models (DLRMs) have become an essential component of many modern recommender systems. Several companies are now building large compute clusters reserved only for DLRM training, driving new interest in cost- & time- saving optimizations. The systems challenges faced in this setting are unique; while typical deep learning (DL) training jobs are dominated by model execution times, the most important factor in DLRM training performance is often online data ingestion.